Biology subjects

van Beers, R. J.

Publications and source records attributed to van Beers, R. J..

11 recordsLinked to original sources

bioRxiv2026

Motor effort biases perceptual decisions through later-stage evidence accumulation rather than early sensory-attentional processing

Motor effort has been shown to bias perceptual decisions toward less effortful choices, but it remains unknown whether this bias already takes effect during the early stages of decision formation through preparatory attentional allocation or sensory processing, or during later-stage evidence accumulation preceding response execution. This study investigated when motor effort becomes integrated into decision formation by focusing on the temporal evolution of neural processing during perceptual decision-making. While 64-channel EEG was recorded, twenty-four healthy adults performed an orientation discrimination task in which two Gabor patches appeared simultaneously in the left and right visual hemifield and decisions were reported using two pressure-sensitive response buttons requiring different levels of force. We found that motor effort modulated EEG activity at both the preparatory and later decision stages: pre-stimulus alpha power was reduced over the occipito-parietal cortex contralateral to the low-effort option, and mean centro-parietal positivity (CPP) amplitude preceding response execution was greater over centro-parietal cortex for low-effort choices, while leaving early sensory representations intact as indicated by no differences in P1 or N1 amplitude following stimulus onset. Trial-by-trial CPP amplitude preceding response execution increased with the likelihood of selecting the low-effort option, whereas the pre-stimulus alpha modulation was not associated with behavioral decision bias. These findings suggest that motor effort biases perceptual decisions primarily during later-stage evidence accumulation, thereby providing insight into the neural basis of embodied perceptual decision making.

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bioRxiv2025

How Prior Motor States Can Shape Perceptual Decision Bias: Insights from Sensorimotor Beta Oscillations

Emerging evidence suggests that decision making is not a purely cognitive process preceding motor output but rather an embodied phenomenon in which the sensorimotor system actively shapes choice selection. Beta oscillations (13-30 Hz) over left and right sensorimotor cortex have been shown to encode motor action and exert inhibitory influence through lateralization of the post-movement rebound, biasing subsequent decisions toward responses with the other hand. This study investigated whether sensorimotor beta oscillations elicited by an isolated choice-unrelated motor action could influence a subsequent perceptual decision. Twenty-nine healthy adults (25 right-handed) completed a two-stage task while 64-channel EEG was recorded. In each trial, participants executed an initial button press with either the left or right thumb to a letter cue ("L" or "R") followed by, after a variable delay (0.5, 1.2 or 3 s), a briefly presented visual grating requiring a decision response on the orientation of the grating via a second button press. We computed the degree of beta power lateralization between left and right (pre-) motor cortical sources that was present during presentation of the grating stimulus and quantified choice bias as the threshold difference between psychometric curves fitted to left-versus right-initial response trials. Participants with stronger beta lateralization during stimulus presentation showed a greater tendency to alternate their decision response from the hand used for the initial button press and exhibited slower decision speeds. However, we failed to detect a significant group-level decision bias induced by the initial motor action, nor were there consistent within-subject correlations between decision bias and beta lateralization across delays. Following the perspective of embodied-decision making, our results partially support the influence of motor cortex activity on the choice process, while also suggesting that beta activity may serve as a trait-like index of individual susceptibility to decision bias.

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bioRxiv2025

Does stimulus order affect central tendency and serial dependence in vestibular path integration?

The reproduction of a perceived stimulus, such as a distance or a duration, is often influenced by two biases. Central tendency indicates that reproductions are biased toward the mean of the stimulus distribution. Serial dependence reflects that the reproduction of the current stimulus is influenced by the previous stimulus. Although these biases are well-documented, their origins remain to be determined. Studies on duration reproduction suggest that autocorrelation within a stimulus sequence may play a role. In this study, we explored whether the level of autocorrelation in a stimulus sequence affects central tendency and serial dependence in vestibular path integration. Participants (n = 24) performed a vestibular distance reproduction task in total darkness by actively replicating a passively moved stimulus distance with a linear motion platform. We compared two conditions: a high-autocorrelation condition, where stimulus distances followed a random walk, and a no-autocorrelation condition, where the same distances were presented in a randomly shuffled order. We quantified both biases using two approaches: separate simple linear regressions and a joint multiple linear regression model that accounts for the autocorrelation in the stimulus sequence. Simple linear regressions revealed that central tendency was weaker and serial dependence reversed in the high-autocorrelation condition compared to the no-autocorrelation condition. However, these differences were no longer observed in the multiple linear regression analysis, indicating that these biases were independent of the specific stimulus sequence protocol. We conclude that these perceptual biases in vestibular path integration persist regardless of stimulus autocorrelation, suggesting that they reflect robust strategies of the brain to process vestibular information in self-motion perception. Author summaryHow are we able to successfully navigate our surroundings? An essential part of navigation is distance estimation based on self-motion signals. We previously found that distance reproductions based on vestibular self-motion signals were affected by stimulus history. Reproductions showed a central tendency toward the mean of the stimulus distribution and an attractive serial dependence toward the immediately preceding stimulus distance. The stimulus distances were presented in a low-autocorrelation, randomized order. Here we ask whether reproductions show the same central tendency and serial dependence when consecutive stimulus distances are similar (i.e., in a high-autocorrelation, random-walk order). Participants performed a distance reproduction task in the dark: a linear motion platform first passively moved the participant over a stimulus distance, after which they actively reproduced this distance by steering the platform back to the estimated start position. We found that the reproductions showed similar central tendency and attractive serial dependence in both a no- and high-autocorrelation condition, but only if the analysis accounted for the covariation of the two effects in the high-autocorrelation condition. In conclusion, our findings indicate that central tendency and serial dependence of vestibular distance reproductions are not a result of the stimulus sequence protocol, but have neurocognitive origins.

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bioRxiv2024

Central tendency and serial dependence in vestibular path integration

Path integration, the process of updating ones position using successive self-motion signals, has previously been studied using visual distance reproduction tasks in which optic flow patterns provide information about traveled distance. These studies have reported that reproduced distances show two types of systematic biases: central tendency and serial dependence. In the present study, we investigated whether these biases are also present in vestibular path integration. Participants were seated on a linear motion platform and performed a distance reproduction task in total darkness. The platform first passively moved the participant a pre-defined stimulus distance which they then actively reproduced by steering the platform back the same distance. Stimulus distances were sampled from short- and long-distance probability distributions and presented in either a randomized order or in separate blocks to study the effect of presentation context. Similar to the effects observed in visual path integration, we found that reproduced distances showed an overall positive central tendency effect as well as a positive, attractive serial dependence effect. Furthermore, reproduction behavior was affected by presentation context. These results were mostly consistent with predictions of a Bayesian Kalman-filter model, originally proposed for visual path integration. New & NoteworthyDistance reproduction tasks based on visual information about the traveled distance have shown that reproductions are biased by central tendency and serial dependence effects. Here, we show that distance reproductions based on vestibular signals show similar biases and that the reproductions are affected by the presentation order of the stimulus distances.

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bioRxiv2024

Does early-stage Alzheimer's disease affect the dynamics of motor adaptation?

Alzheimers disease (AD) is characterized by an initial decline in declarative memory, while non-declarative memory processing remains relatively intact. Error-based motor adaptation is traditionally seen as a form of non-declarative memory, but recent findings suggest that it involves both fast, declarative and slow, non-declarative adaptive processes. If the declarative memory system shares resources with the fast process in motor adaptation, it can be hypothesized that the fast, but not the slow, process is disturbed in AD patients. To test this, we studied 20 early-stage AD patients and 21 age-matched controls of both sexes using a reach adaptation paradigm that relies on spontaneous recovery after sequential exposure to opposing force fields. Adaptation was measured using error clamps and expressed as an adaptation index (AI). Although patients with AD showed slightly lower adaptation to the force field than the controls, both groups demonstrated effects of spontaneous recovery. The time course of the AI was fitted by a hierarchical Bayesian two-state model in which each dynamic state is characterized by a retention and learning rate. Compared to controls, the retention rate of the fast process was the only parameter that was significantly different (lower) in the AD patients, confirming that the memory of the declarative, fast process is disturbed by AD. The slow adaptive process was virtually unaffected. Since the slow process learns only weakly from error, our results provide neurocomputational evidence for the clinical practice of errorless learning of everyday tasks in people with dementia.

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bioRxiv2022

Natural statistics of head roll: implications for Bayesian inference in spatial orientation

We previously proposed a Bayesian model of multisensory integration in spatial orientation (1). Using a Gaussian prior, centered on an upright head orientation, this model could explain various perceptual observations in roll-tilted participants, such as the subjective visual vertical, the subjective body tilt (1), the rod-and-frame effect (2), as well as their clinical (3) and age-related deficits (4). Because it is generally assumed that the prior reflects an accumulated history of previous head orientations, and recent work on natural head motion suggests non-Gaussian statistics, we examined how the model would perform with a non-Gaussian prior. In the present study, we first experimentally generalized the previous observations in showing that also the natural statistics of head orientation are characterized by long tails, best quantified as a t-location-scale distribution. Next, we compared the performance of the Bayesian model and various model variants using such a t-distributed prior to the original model with the Gaussian prior on their accounts of previously published data of the subjective visual vertical and subjective body tilt tasks. All of these variants performed substantially worse than the original model, suggesting a special value of the Gaussian prior. We provide computational and neurophysiological reasons for the implementation of such a prior, in terms of its associated precision-accuracy trade-off in vertical perception across the tilt range. New & NoteworthyIt has been argued that the brain uses Bayesian computations to process multiple sensory cues in vertical perception, including a prior centered on upright head orientation which is usually taken to be Gaussian. Here, we show that non-Gaussian prior distributions, although more akin to the statistics of head orientation during natural activities, provide a much worse explanation of such perceptual observations than a Gaussian prior.

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bioRxiv2022

Predictive steering: Integration of artificial motor signals in self-motion estimation

The brains computations for active and passive self-motion estimation can be unified with a single model that optimally combines vestibular and visual signals with sensory predictions based on motor efference copies. It is unknown whether this theoretical framework also applies to the integration of artificial motor signals, like the motor signals that occur when driving a car. Here, we examined if training humans to control a self-motion platform would lead to the construction of an accurate internal model of the mapping between the steering movement and the vestibular reafference. Participants (n = 15) were seated on a linear motion platform and actively controlled the platforms velocity using a steering wheel to translate their body to a memorized visual target location (Motion condition). We compared their steering behavior to that of participants (n = 15) who remained stationary and instead aligned a non-visible line with the target (Stationary condition). To probe learning, the gain between the steering wheel angle and the platform velocity or line velocity changed abruptly twice during the experiment. These gain changes were virtually undetectable in the displacement error in the Motion condition, whereas clear deviations were observed in the Stationary condition. These results show that participants in the Motion condition made within-trial changes to their steering behavior immediately after the gain changes. This suggests that they continuously compared the vestibular reafference to internal predictions, and thus employed and updated an internal forward model of the mapping between the steering movement and the vestibular reafference. New & NoteworthyPerception of self-motion is known to depend on the integration of sensory signals and, when the motion is self-generated, the predicted sensory reafference based on motor efference copies. Here we show, using a closed-loop steering experiment with a direct coupling between the steering movement and the vestibular self-motion feedback, that humans are also able to integrate artificial motor signals, like the motor signals that occur when driving a car.

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bioRxiv2021

Even well-practiced movements benefit from repetition

Professional golf players spend years practicing, but will still perform one or two practice swings without a ball before executing the actual swing. Why do they do this? In this study we tested the hypothesis that repeating a well-practiced movement leads to a reduction of movement variability. To operationalize this hypothesis, participants were tested in a center- out reaching task with four different targets, on four different days. To probe the effect of repetition they performed random sequences from one to six movements to the same target. Our findings show that, with repetition, movements are not only initiated earlier but their variability is reduced across the entire movement trajectory. Furthermore, this effect is present within and across the four sessions. Together, our results suggest that movement repetition changes the tradeoff between movement initiation and movement precision. New & NoteworthyProfessional athletes practice movements that they have performed thousands of times in training just before it is their turn in a game. Why do they do this? Our results indicate that both initial and endpoint variability reduce with repetition in a short sequence of reaching movements. This means that even well-practiced movements benefit from practice.

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bioRxiv2021

Sensitivity to Error During Visuomotor Adaptation is Similarly Modulated by Abrupt, Gradual and Random Perturbation Schedules

It has been suggested that sensorimotor adaptation involves at least two processes (i.e., fast and slow) that differ in retention and error sensitivity. Previous work has shown that repeated exposure to an abrupt force field perturbation results in greater error sensitivity for both the fast and slow processes. While this implies that the faster relearning is associated with increased error sensitivity, it remains unclear what aspects of prior experience modulate error sensitivity. In the present study, we manipulated the initial training using different perturbation schedules, thought to differentially affect fast and slow learning processes based on error magnitude, and then observed what effect prior learning had on subsequent adaptation. During initial training of a visuomotor rotation task, we exposed three groups of participants to either an abrupt, a gradual, or a random perturbation schedule. During a testing session, all three groups were subsequently exposed to an abrupt perturbation schedule. Comparing the two sessions of the control group who experienced repetition of the same perturbation, we found an increased error sensitivity for both processes. We found that the error sensitivity was increased for both the fast and slow processes, with no reliable changes in the retention, for both the gradual and structural learning groups when compared to the first session of the control group. We discuss the findings in the context of how fast and slow learning processes respond to a history of errors. New & NoteworthyWe investigated what aspects of prior experience modulate error sensitivity, within the framework of a two-state model of short-term sensorimotor adaptation. We manipulated initial training on a visuomotor adaptation reaching task using specific perturbation schedules that are thought to differentially affect fast and slow learning processes, and we tested what effect these had on subsequent adaptation. We found that sensitivity to adaptation error was similarly modulated by abrupt, gradual, and random perturbation schedules.

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bioRxiv2018

Prediction and final temporal errors are used for trial-to-trial motor corrections

Many daily life situations (e.g. dodging an approaching object or hitting a moving target) require people to correct planning of future movements based on previous temporal errors. However, the actual temporal error can be difficult to perceive: imagine a baseball batter that swings and misses a fastball. Here we show that in such situations people can use an internal error signal to make corrections in the next trial. This signal is based on the discrepancy between the actual and the planned action onset time: the prediction error. In this study, we used three interception tasks: reaching movements, saccadic eye movements and a button press that released a cursor moving ballistically for a fixed time. We found that action onset depended on the previous temporal error in the arm movement experiment only and not in the saccadic and button press experiments. However, this dependency was modulated by the movement time: faster arm movements depended less on the previous actual temporal error. An analysis using a Kalman filter confirmed that people used the prediction error rather than the previous temporal error for trial-by-trial corrections in fast arm movements, saccades and button press.

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bioRxiv2017

Bayesian adaptive stimulus selection for dissociating models of psychophysical data

Comparing models facilitates testing different hypotheses regarding the computational basis of perception and action. Effective model comparison requires stimuli for which models make different predictions. Typically, experiments use a predetermined set of stimuli or sample stimuli randomly. Both methods have limitations; a predetermined set may not contain stimuli that dissociate the models whereas random sampling may be inefficient. To overcome these limitations, we expanded the psi-algorithm (Kontsevich & Tyler, 1999) from estimating the parameters of a psychometric curve to distinguishing models. To test our algorithm, we applied it to two distinct problems. First, we investigated dissociating sensory noise models. We simulated ideal observers with different noise models performing a 2-afc task. Stimuli were selected randomly or using our algorithm. We found using our algorithm improved the accuracy of model comparison. We also validated the algorithm in subjects by inferring which noise model underlies speed perception. Our algorithm converged quickly to the model previously proposed (Stocker & Simoncelli, 2006), whereas if stimuli were selected randomly model probabilities separated slower and sometimes supported alternative models. Second, we applied our algorithm to a different problem; comparing models of target selection under body acceleration. Previous work found target choice preference is modulated by whole body acceleration (Rincon-Gonzalez et al., 2016). However, the effect is subtle making model comparison difficult. We show that selecting stimuli adaptively could have led to stronger conclusions in model comparison. We conclude that our technique is more efficient and more reliable than current methods of stimulus selection for dissociating models.\n\nData AvailabilityAll data and code will be posted on our institutional repository system following acceptance. In the meantime feel free to contact the authors if you would like any of the code.

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